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<div class="header">
  <div class="summary">
<a href="#pub-types">Public 类型</a> &#124;
<a href="#pub-methods">Public 成员函数</a> &#124;
<a href="#pro-attribs">Protected 属性</a> &#124;
<a href="classpcl_1_1people_1_1_ground_based_people_detection_app-members.html">所有成员列表</a>  </div>
  <div class="headertitle">
<div class="title">pcl::people::GroundBasedPeopleDetectionApp&lt; PointT &gt; 模板类 参考</div>  </div>
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<p><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html" title="GroundBasedPeopleDetectionApp performs people detection on RGB-D data having as input the ground plan...">GroundBasedPeopleDetectionApp</a> performs people detection on RGB-D data having as input the ground plane coefficients. It implements the people detection algorithm described here: M. Munaro, F. Basso and E. Menegatti, Tracking people within groups with RGB-D data, In Proceedings of the International Conference on Intelligent Robots and Systems (IROS) 2012, Vilamoura (Portugal), 2012.  
 <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#details">更多...</a></p>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-types"></a>
Public 类型</h2></td></tr>
<tr class="memitem:af1a2d5d800c30d1a220fbc8cc03ddfb9"><td class="memItemLeft" align="right" valign="top"><a id="af1a2d5d800c30d1a220fbc8cc03ddfb9"></a>
typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloud</b></td></tr>
<tr class="separator:af1a2d5d800c30d1a220fbc8cc03ddfb9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:abf8d9e47f003698b973a5df0bd259cd1"><td class="memItemLeft" align="right" valign="top"><a id="abf8d9e47f003698b973a5df0bd259cd1"></a>
typedef boost::shared_ptr&lt; <a class="el" href="classpcl_1_1_point_cloud.html">PointCloud</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudPtr</b></td></tr>
<tr class="separator:abf8d9e47f003698b973a5df0bd259cd1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab36fdd870d3f79f9739d2c51791fb9b0"><td class="memItemLeft" align="right" valign="top"><a id="ab36fdd870d3f79f9739d2c51791fb9b0"></a>
typedef boost::shared_ptr&lt; const <a class="el" href="classpcl_1_1_point_cloud.html">PointCloud</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudConstPtr</b></td></tr>
<tr class="separator:ab36fdd870d3f79f9739d2c51791fb9b0"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public 成员函数</h2></td></tr>
<tr class="memitem:a13fd5a5b9f2c03d75a303f2d1fffca79"><td class="memItemLeft" align="right" valign="top"><a id="a13fd5a5b9f2c03d75a303f2d1fffca79"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a13fd5a5b9f2c03d75a303f2d1fffca79">GroundBasedPeopleDetectionApp</a> ()</td></tr>
<tr class="memdesc:a13fd5a5b9f2c03d75a303f2d1fffca79"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor. <br /></td></tr>
<tr class="separator:a13fd5a5b9f2c03d75a303f2d1fffca79"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae2a57b74d01adf84f8371ffc5d8cb4cd"><td class="memItemLeft" align="right" valign="top"><a id="ae2a57b74d01adf84f8371ffc5d8cb4cd"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ae2a57b74d01adf84f8371ffc5d8cb4cd">~GroundBasedPeopleDetectionApp</a> ()</td></tr>
<tr class="memdesc:ae2a57b74d01adf84f8371ffc5d8cb4cd"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor. <br /></td></tr>
<tr class="separator:ae2a57b74d01adf84f8371ffc5d8cb4cd"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4d891de9e757b98155a630ac7a7c9de7"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a4d891de9e757b98155a630ac7a7c9de7">setInputCloud</a> (PointCloudPtr &amp;cloud)</td></tr>
<tr class="memdesc:a4d891de9e757b98155a630ac7a7c9de7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the pointer to the input cloud.  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a4d891de9e757b98155a630ac7a7c9de7">更多...</a><br /></td></tr>
<tr class="separator:a4d891de9e757b98155a630ac7a7c9de7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6ad2ce897659e25fd5552be5cfcebd50"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a6ad2ce897659e25fd5552be5cfcebd50">setGround</a> (Eigen::VectorXf &amp;ground_coeffs)</td></tr>
<tr class="memdesc:a6ad2ce897659e25fd5552be5cfcebd50"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the ground coefficients.  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a6ad2ce897659e25fd5552be5cfcebd50">更多...</a><br /></td></tr>
<tr class="separator:a6ad2ce897659e25fd5552be5cfcebd50"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:abb1e96641bf0cd5d87ec9d32181a3efa"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#abb1e96641bf0cd5d87ec9d32181a3efa">setTransformation</a> (const Eigen::Matrix3f &amp;transformation)</td></tr>
<tr class="memdesc:abb1e96641bf0cd5d87ec9d32181a3efa"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the transformation matrix, which is used in order to transform the given point cloud, the ground plane and the intrinsics matrix to the internal coordinate frame.  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#abb1e96641bf0cd5d87ec9d32181a3efa">更多...</a><br /></td></tr>
<tr class="separator:abb1e96641bf0cd5d87ec9d32181a3efa"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a19a15f63fc6648a65d54e2d70e6dbd7e"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a19a15f63fc6648a65d54e2d70e6dbd7e">setSamplingFactor</a> (int sampling_factor)</td></tr>
<tr class="memdesc:a19a15f63fc6648a65d54e2d70e6dbd7e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set sampling factor.  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a19a15f63fc6648a65d54e2d70e6dbd7e">更多...</a><br /></td></tr>
<tr class="separator:a19a15f63fc6648a65d54e2d70e6dbd7e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5280579c14550268bd5b64a01f5716b5"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a5280579c14550268bd5b64a01f5716b5">setVoxelSize</a> (float voxel_size)</td></tr>
<tr class="memdesc:a5280579c14550268bd5b64a01f5716b5"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set voxel size.  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a5280579c14550268bd5b64a01f5716b5">更多...</a><br /></td></tr>
<tr class="separator:a5280579c14550268bd5b64a01f5716b5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a915f68c8aa39a15fc5a129a6d87b00a5"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a915f68c8aa39a15fc5a129a6d87b00a5">setIntrinsics</a> (Eigen::Matrix3f intrinsics_matrix)</td></tr>
<tr class="memdesc:a915f68c8aa39a15fc5a129a6d87b00a5"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set intrinsic parameters of the <a class="el" href="structpcl_1_1_r_g_b.html" title="A structure representing RGB color information.">RGB</a> camera.  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a915f68c8aa39a15fc5a129a6d87b00a5">更多...</a><br /></td></tr>
<tr class="separator:a915f68c8aa39a15fc5a129a6d87b00a5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a31940f8ad83752c91fed13ef030bf714"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a31940f8ad83752c91fed13ef030bf714">setClassifier</a> (<a class="el" href="classpcl_1_1people_1_1_person_classifier.html">pcl::people::PersonClassifier</a>&lt; <a class="el" href="structpcl_1_1_r_g_b.html">pcl::RGB</a> &gt; person_classifier)</td></tr>
<tr class="memdesc:a31940f8ad83752c91fed13ef030bf714"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set SVM-based person classifier.  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a31940f8ad83752c91fed13ef030bf714">更多...</a><br /></td></tr>
<tr class="separator:a31940f8ad83752c91fed13ef030bf714"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa863e592db0f6d0e943f11a1ee93b564"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aa863e592db0f6d0e943f11a1ee93b564">setFOV</a> (float min, float max)</td></tr>
<tr class="memdesc:aa863e592db0f6d0e943f11a1ee93b564"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the field of view of the point cloud in z direction.  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aa863e592db0f6d0e943f11a1ee93b564">更多...</a><br /></td></tr>
<tr class="separator:aa863e592db0f6d0e943f11a1ee93b564"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af5662950e81c30873915ed91dcc0d0d2"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af5662950e81c30873915ed91dcc0d0d2">setSensorPortraitOrientation</a> (bool vertical)</td></tr>
<tr class="memdesc:af5662950e81c30873915ed91dcc0d0d2"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set sensor orientation (vertical = true means portrait mode, vertical = false means landscape mode).  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af5662950e81c30873915ed91dcc0d0d2">更多...</a><br /></td></tr>
<tr class="separator:af5662950e81c30873915ed91dcc0d0d2"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a31b917712ffe4f66d8ecf85ee9e71749"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a31b917712ffe4f66d8ecf85ee9e71749">setHeadCentroid</a> (bool head_centroid)</td></tr>
<tr class="memdesc:a31b917712ffe4f66d8ecf85ee9e71749"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set head_centroid_ to true (person centroid is in the head) or false (person centroid is the whole body centroid).  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a31b917712ffe4f66d8ecf85ee9e71749">更多...</a><br /></td></tr>
<tr class="separator:a31b917712ffe4f66d8ecf85ee9e71749"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab089c9fe913edf8b5aff9d9e64f6914a"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ab089c9fe913edf8b5aff9d9e64f6914a">setPersonClusterLimits</a> (float min_height, float max_height, float min_width, float max_width)</td></tr>
<tr class="memdesc:ab089c9fe913edf8b5aff9d9e64f6914a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set minimum and maximum allowed height and width for a person cluster.  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ab089c9fe913edf8b5aff9d9e64f6914a">更多...</a><br /></td></tr>
<tr class="separator:ab089c9fe913edf8b5aff9d9e64f6914a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2c906736068e8325c05243de6460dba4"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a2c906736068e8325c05243de6460dba4">setMinimumDistanceBetweenHeads</a> (float heads_minimum_distance)</td></tr>
<tr class="memdesc:a2c906736068e8325c05243de6460dba4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set minimum distance between persons' heads.  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a2c906736068e8325c05243de6460dba4">更多...</a><br /></td></tr>
<tr class="separator:a2c906736068e8325c05243de6460dba4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a96dd362f2971dab29b62c02ebf0a4ad2"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a96dd362f2971dab29b62c02ebf0a4ad2">getPersonClusterLimits</a> (float &amp;min_height, float &amp;max_height, float &amp;min_width, float &amp;max_width)</td></tr>
<tr class="memdesc:a96dd362f2971dab29b62c02ebf0a4ad2"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the minimum and maximum allowed height and width for a person cluster.  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a96dd362f2971dab29b62c02ebf0a4ad2">更多...</a><br /></td></tr>
<tr class="separator:a96dd362f2971dab29b62c02ebf0a4ad2"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a00e3e22879cc58458e8bc1d57f1f0b4c"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a00e3e22879cc58458e8bc1d57f1f0b4c">getDimensionLimits</a> (int &amp;min_points, int &amp;max_points)</td></tr>
<tr class="memdesc:a00e3e22879cc58458e8bc1d57f1f0b4c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get minimum and maximum allowed number of points for a person cluster.  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a00e3e22879cc58458e8bc1d57f1f0b4c">更多...</a><br /></td></tr>
<tr class="separator:a00e3e22879cc58458e8bc1d57f1f0b4c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aca14cbeff3ce425e9a8fe3170236da77"><td class="memItemLeft" align="right" valign="top"><a id="aca14cbeff3ce425e9a8fe3170236da77"></a>
float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aca14cbeff3ce425e9a8fe3170236da77">getMinimumDistanceBetweenHeads</a> ()</td></tr>
<tr class="memdesc:aca14cbeff3ce425e9a8fe3170236da77"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get minimum distance between persons' heads. <br /></td></tr>
<tr class="separator:aca14cbeff3ce425e9a8fe3170236da77"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa5e5282899e9ef0bd92f37d87cf9cb33"><td class="memItemLeft" align="right" valign="top"><a id="aa5e5282899e9ef0bd92f37d87cf9cb33"></a>
Eigen::VectorXf&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aa5e5282899e9ef0bd92f37d87cf9cb33">getGround</a> ()</td></tr>
<tr class="memdesc:aa5e5282899e9ef0bd92f37d87cf9cb33"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get floor coefficients. <br /></td></tr>
<tr class="separator:aa5e5282899e9ef0bd92f37d87cf9cb33"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4e007039016b8be76f00495a6d114095"><td class="memItemLeft" align="right" valign="top"><a id="a4e007039016b8be76f00495a6d114095"></a>
PointCloudPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a4e007039016b8be76f00495a6d114095">getFilteredCloud</a> ()</td></tr>
<tr class="memdesc:a4e007039016b8be76f00495a6d114095"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the filtered point cloud. <br /></td></tr>
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<tr class="memitem:a0136956b003c924a34bbbe02a032a4d4"><td class="memItemLeft" align="right" valign="top"><a id="a0136956b003c924a34bbbe02a032a4d4"></a>
PointCloudPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a0136956b003c924a34bbbe02a032a4d4">getNoGroundCloud</a> ()</td></tr>
<tr class="memdesc:a0136956b003c924a34bbbe02a032a4d4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get pointcloud after voxel grid filtering and ground removal. <br /></td></tr>
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<tr class="memitem:a1d2f9ad79adf98c4bfc5c156d97b12b8"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a1d2f9ad79adf98c4bfc5c156d97b12b8">extractRGBFromPointCloud</a> (PointCloudPtr input_cloud, <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_r_g_b.html">pcl::RGB</a> &gt;::Ptr &amp;output_cloud)</td></tr>
<tr class="memdesc:a1d2f9ad79adf98c4bfc5c156d97b12b8"><td class="mdescLeft">&#160;</td><td class="mdescRight">Extract <a class="el" href="structpcl_1_1_r_g_b.html" title="A structure representing RGB color information.">RGB</a> information from a point cloud and output the corresponding <a class="el" href="structpcl_1_1_r_g_b.html" title="A structure representing RGB color information.">RGB</a> point cloud.  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a1d2f9ad79adf98c4bfc5c156d97b12b8">更多...</a><br /></td></tr>
<tr class="separator:a1d2f9ad79adf98c4bfc5c156d97b12b8"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a60516702b769124ed3da3fd318258ba0"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a60516702b769124ed3da3fd318258ba0">swapDimensions</a> (<a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_r_g_b.html">pcl::RGB</a> &gt;::Ptr &amp;cloud)</td></tr>
<tr class="memdesc:a60516702b769124ed3da3fd318258ba0"><td class="mdescLeft">&#160;</td><td class="mdescRight">Swap rows/cols dimensions of a <a class="el" href="structpcl_1_1_r_g_b.html" title="A structure representing RGB color information.">RGB</a> point cloud (90 degrees counterclockwise rotation).  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a60516702b769124ed3da3fd318258ba0">更多...</a><br /></td></tr>
<tr class="separator:a60516702b769124ed3da3fd318258ba0"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a74d6d3cb5fd914ed35b0d23702719912"><td class="memItemLeft" align="right" valign="top"><a id="a74d6d3cb5fd914ed35b0d23702719912"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a74d6d3cb5fd914ed35b0d23702719912">updateMinMaxPoints</a> ()</td></tr>
<tr class="memdesc:a74d6d3cb5fd914ed35b0d23702719912"><td class="mdescLeft">&#160;</td><td class="mdescRight">Estimates min_points_ and max_points_ based on the minimal and maximal cluster size and the voxel size. <br /></td></tr>
<tr class="separator:a74d6d3cb5fd914ed35b0d23702719912"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8aee7a6add005a4c42ade573585acfff"><td class="memItemLeft" align="right" valign="top"><a id="a8aee7a6add005a4c42ade573585acfff"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a8aee7a6add005a4c42ade573585acfff">applyTransformationPointCloud</a> ()</td></tr>
<tr class="memdesc:a8aee7a6add005a4c42ade573585acfff"><td class="mdescLeft">&#160;</td><td class="mdescRight">Applies the transformation to the input point cloud. <br /></td></tr>
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<tr class="memitem:ad88876b8e9f69b703ffc26d1d5c92760"><td class="memItemLeft" align="right" valign="top"><a id="ad88876b8e9f69b703ffc26d1d5c92760"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ad88876b8e9f69b703ffc26d1d5c92760">applyTransformationGround</a> ()</td></tr>
<tr class="memdesc:ad88876b8e9f69b703ffc26d1d5c92760"><td class="mdescLeft">&#160;</td><td class="mdescRight">Applies the transformation to the ground plane. <br /></td></tr>
<tr class="separator:ad88876b8e9f69b703ffc26d1d5c92760"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0dc924992669bcd76b7dad68cfd5c5f6"><td class="memItemLeft" align="right" valign="top"><a id="a0dc924992669bcd76b7dad68cfd5c5f6"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a0dc924992669bcd76b7dad68cfd5c5f6">applyTransformationIntrinsics</a> ()</td></tr>
<tr class="memdesc:a0dc924992669bcd76b7dad68cfd5c5f6"><td class="mdescLeft">&#160;</td><td class="mdescRight">Applies the transformation to the intrinsics matrix. <br /></td></tr>
<tr class="separator:a0dc924992669bcd76b7dad68cfd5c5f6"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a06ab91072245185aefb01e9f7c5f53bf"><td class="memItemLeft" align="right" valign="top"><a id="a06ab91072245185aefb01e9f7c5f53bf"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a06ab91072245185aefb01e9f7c5f53bf">filter</a> ()</td></tr>
<tr class="memdesc:a06ab91072245185aefb01e9f7c5f53bf"><td class="mdescLeft">&#160;</td><td class="mdescRight">Reduces the input cloud to one point per voxel and limits the field of view. <br /></td></tr>
<tr class="separator:a06ab91072245185aefb01e9f7c5f53bf"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aef52be2a667ceb8c1c58b93c06125fa0"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aef52be2a667ceb8c1c58b93c06125fa0">compute</a> (std::vector&lt; <a class="el" href="classpcl_1_1people_1_1_person_cluster.html">pcl::people::PersonCluster</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &gt; &amp;clusters)</td></tr>
<tr class="memdesc:aef52be2a667ceb8c1c58b93c06125fa0"><td class="mdescLeft">&#160;</td><td class="mdescRight">Perform people detection on the input data and return people clusters information.  <a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aef52be2a667ceb8c1c58b93c06125fa0">更多...</a><br /></td></tr>
<tr class="separator:aef52be2a667ceb8c1c58b93c06125fa0"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-attribs"></a>
Protected 属性</h2></td></tr>
<tr class="memitem:afbf9a72fb4d539a13c14e49459a8a921"><td class="memItemLeft" align="right" valign="top"><a id="afbf9a72fb4d539a13c14e49459a8a921"></a>
int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#afbf9a72fb4d539a13c14e49459a8a921">sampling_factor_</a></td></tr>
<tr class="memdesc:afbf9a72fb4d539a13c14e49459a8a921"><td class="mdescLeft">&#160;</td><td class="mdescRight">sampling factor used to downsample the point cloud <br /></td></tr>
<tr class="separator:afbf9a72fb4d539a13c14e49459a8a921"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9dfb9076a6111ff4588a554d83ef9971"><td class="memItemLeft" align="right" valign="top"><a id="a9dfb9076a6111ff4588a554d83ef9971"></a>
float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a9dfb9076a6111ff4588a554d83ef9971">voxel_size_</a></td></tr>
<tr class="memdesc:a9dfb9076a6111ff4588a554d83ef9971"><td class="mdescLeft">&#160;</td><td class="mdescRight">voxel size <br /></td></tr>
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<tr class="memitem:aa72a39059ffc190840f21eff697fb40f"><td class="memItemLeft" align="right" valign="top"><a id="aa72a39059ffc190840f21eff697fb40f"></a>
Eigen::VectorXf&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aa72a39059ffc190840f21eff697fb40f">ground_coeffs_</a></td></tr>
<tr class="memdesc:aa72a39059ffc190840f21eff697fb40f"><td class="mdescLeft">&#160;</td><td class="mdescRight">ground plane coefficients <br /></td></tr>
<tr class="separator:aa72a39059ffc190840f21eff697fb40f"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af2cab2d3c83b79a7004eec888fe37e57"><td class="memItemLeft" align="right" valign="top"><a id="af2cab2d3c83b79a7004eec888fe37e57"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af2cab2d3c83b79a7004eec888fe37e57">ground_coeffs_set_</a></td></tr>
<tr class="memdesc:af2cab2d3c83b79a7004eec888fe37e57"><td class="mdescLeft">&#160;</td><td class="mdescRight">flag stating whether the ground coefficients have been set or not <br /></td></tr>
<tr class="separator:af2cab2d3c83b79a7004eec888fe37e57"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa6fce363d05279c79d9f441f731babd2"><td class="memItemLeft" align="right" valign="top"><a id="aa6fce363d05279c79d9f441f731babd2"></a>
Eigen::VectorXf&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aa6fce363d05279c79d9f441f731babd2">ground_coeffs_transformed_</a></td></tr>
<tr class="memdesc:aa6fce363d05279c79d9f441f731babd2"><td class="mdescLeft">&#160;</td><td class="mdescRight">the transformed ground coefficients <br /></td></tr>
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<tr class="memitem:a995fba929fa9febd580581fe143a3521"><td class="memItemLeft" align="right" valign="top"><a id="a995fba929fa9febd580581fe143a3521"></a>
float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a995fba929fa9febd580581fe143a3521">sqrt_ground_coeffs_</a></td></tr>
<tr class="memdesc:a995fba929fa9febd580581fe143a3521"><td class="mdescLeft">&#160;</td><td class="mdescRight">ground plane normalization factor <br /></td></tr>
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<tr class="memitem:ad38c3910bab88bbc45151ae6ec34fa9e"><td class="memItemLeft" align="right" valign="top"><a id="ad38c3910bab88bbc45151ae6ec34fa9e"></a>
Eigen::Matrix3f&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ad38c3910bab88bbc45151ae6ec34fa9e">transformation_</a></td></tr>
<tr class="memdesc:ad38c3910bab88bbc45151ae6ec34fa9e"><td class="mdescLeft">&#160;</td><td class="mdescRight">rotation matrix which transforms input point cloud to internal people tracker coordinate frame <br /></td></tr>
<tr class="separator:ad38c3910bab88bbc45151ae6ec34fa9e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3755cf5e032e685eab28df94aa14113c"><td class="memItemLeft" align="right" valign="top"><a id="a3755cf5e032e685eab28df94aa14113c"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a3755cf5e032e685eab28df94aa14113c">transformation_set_</a></td></tr>
<tr class="memdesc:a3755cf5e032e685eab28df94aa14113c"><td class="mdescLeft">&#160;</td><td class="mdescRight">flag stating whether the transformation matrix has been set or not <br /></td></tr>
<tr class="separator:a3755cf5e032e685eab28df94aa14113c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a48d13a412a7e372b5a913bc861bd30ca"><td class="memItemLeft" align="right" valign="top"><a id="a48d13a412a7e372b5a913bc861bd30ca"></a>
PointCloudPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a48d13a412a7e372b5a913bc861bd30ca">cloud_</a></td></tr>
<tr class="memdesc:a48d13a412a7e372b5a913bc861bd30ca"><td class="mdescLeft">&#160;</td><td class="mdescRight">pointer to the input cloud <br /></td></tr>
<tr class="separator:a48d13a412a7e372b5a913bc861bd30ca"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a13d6dc63906ae29328565f5f42cf2a0d"><td class="memItemLeft" align="right" valign="top"><a id="a13d6dc63906ae29328565f5f42cf2a0d"></a>
PointCloudPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a13d6dc63906ae29328565f5f42cf2a0d">cloud_filtered_</a></td></tr>
<tr class="memdesc:a13d6dc63906ae29328565f5f42cf2a0d"><td class="mdescLeft">&#160;</td><td class="mdescRight">pointer to the filtered cloud <br /></td></tr>
<tr class="separator:a13d6dc63906ae29328565f5f42cf2a0d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5cb6e71a2e30861f0a23804f432fed9a"><td class="memItemLeft" align="right" valign="top"><a id="a5cb6e71a2e30861f0a23804f432fed9a"></a>
PointCloudPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a5cb6e71a2e30861f0a23804f432fed9a">no_ground_cloud_</a></td></tr>
<tr class="memdesc:a5cb6e71a2e30861f0a23804f432fed9a"><td class="mdescLeft">&#160;</td><td class="mdescRight">pointer to the cloud after voxel grid filtering and ground removal <br /></td></tr>
<tr class="separator:a5cb6e71a2e30861f0a23804f432fed9a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af07013f8363c2b3d192f43e11ae7d4e6"><td class="memItemLeft" align="right" valign="top"><a id="af07013f8363c2b3d192f43e11ae7d4e6"></a>
<a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_r_g_b.html">pcl::RGB</a> &gt;::Ptr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af07013f8363c2b3d192f43e11ae7d4e6">rgb_image_</a></td></tr>
<tr class="memdesc:af07013f8363c2b3d192f43e11ae7d4e6"><td class="mdescLeft">&#160;</td><td class="mdescRight">pointer to a <a class="el" href="structpcl_1_1_r_g_b.html" title="A structure representing RGB color information.">RGB</a> cloud corresponding to cloud_ <br /></td></tr>
<tr class="separator:af07013f8363c2b3d192f43e11ae7d4e6"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af2574d41d6960ac7f44b7b988d2b1c21"><td class="memItemLeft" align="right" valign="top"><a id="af2574d41d6960ac7f44b7b988d2b1c21"></a>
float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af2574d41d6960ac7f44b7b988d2b1c21">max_height_</a></td></tr>
<tr class="memdesc:af2574d41d6960ac7f44b7b988d2b1c21"><td class="mdescLeft">&#160;</td><td class="mdescRight">person clusters maximum height from the ground plane <br /></td></tr>
<tr class="separator:af2574d41d6960ac7f44b7b988d2b1c21"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ace264d669fdebef2ca84cf73c588ab50"><td class="memItemLeft" align="right" valign="top"><a id="ace264d669fdebef2ca84cf73c588ab50"></a>
float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ace264d669fdebef2ca84cf73c588ab50">min_height_</a></td></tr>
<tr class="memdesc:ace264d669fdebef2ca84cf73c588ab50"><td class="mdescLeft">&#160;</td><td class="mdescRight">person clusters minimum height from the ground plane <br /></td></tr>
<tr class="separator:ace264d669fdebef2ca84cf73c588ab50"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5db06c5ec4b26cdf2f7658fb347082f9"><td class="memItemLeft" align="right" valign="top"><a id="a5db06c5ec4b26cdf2f7658fb347082f9"></a>
float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a5db06c5ec4b26cdf2f7658fb347082f9">max_width_</a></td></tr>
<tr class="memdesc:a5db06c5ec4b26cdf2f7658fb347082f9"><td class="mdescLeft">&#160;</td><td class="mdescRight">person clusters maximum width, used to estimate how many points maximally represent a person cluster <br /></td></tr>
<tr class="separator:a5db06c5ec4b26cdf2f7658fb347082f9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a07e0d9ca813b18b185606309ee11a7f9"><td class="memItemLeft" align="right" valign="top"><a id="a07e0d9ca813b18b185606309ee11a7f9"></a>
float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a07e0d9ca813b18b185606309ee11a7f9">min_width_</a></td></tr>
<tr class="memdesc:a07e0d9ca813b18b185606309ee11a7f9"><td class="mdescLeft">&#160;</td><td class="mdescRight">person clusters minimum width, used to estimate how many points minimally represent a person cluster <br /></td></tr>
<tr class="separator:a07e0d9ca813b18b185606309ee11a7f9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2f9749e800d83673bcc5f5d7f2643626"><td class="memItemLeft" align="right" valign="top"><a id="a2f9749e800d83673bcc5f5d7f2643626"></a>
float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a2f9749e800d83673bcc5f5d7f2643626">min_fov_</a></td></tr>
<tr class="memdesc:a2f9749e800d83673bcc5f5d7f2643626"><td class="mdescLeft">&#160;</td><td class="mdescRight">the beginning of the field of view in z-direction, should be usually set to zero <br /></td></tr>
<tr class="separator:a2f9749e800d83673bcc5f5d7f2643626"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a50fe9985ffec0898fcdf2863eb620f29"><td class="memItemLeft" align="right" valign="top"><a id="a50fe9985ffec0898fcdf2863eb620f29"></a>
float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a50fe9985ffec0898fcdf2863eb620f29">max_fov_</a></td></tr>
<tr class="memdesc:a50fe9985ffec0898fcdf2863eb620f29"><td class="mdescLeft">&#160;</td><td class="mdescRight">the end of the field of view in z-direction <br /></td></tr>
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<tr class="memitem:afce08127bf56571649bc02755ec2b1b4"><td class="memItemLeft" align="right" valign="top"><a id="afce08127bf56571649bc02755ec2b1b4"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#afce08127bf56571649bc02755ec2b1b4">vertical_</a></td></tr>
<tr class="memdesc:afce08127bf56571649bc02755ec2b1b4"><td class="mdescLeft">&#160;</td><td class="mdescRight">if true, the sensor is considered to be vertically placed (portrait mode) <br /></td></tr>
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bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af72e2f00dace33c58439512a731749f6">head_centroid_</a></td></tr>
<tr class="memdesc:af72e2f00dace33c58439512a731749f6"><td class="mdescLeft">&#160;</td><td class="mdescRight">if true, the person centroid is computed as the centroid of the cluster points belonging to the head; <br  />
 if false, the person centroid is computed as the centroid of the whole cluster points (default = true) <br /></td></tr>
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int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aadfa9db61f00e6284608639649808cee">max_points_</a></td></tr>
<tr class="memdesc:aadfa9db61f00e6284608639649808cee"><td class="mdescLeft">&#160;</td><td class="mdescRight">maximum number of points for a person cluster <br /></td></tr>
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int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af98b404cae60bdcf0833ebaf35aae42c">min_points_</a></td></tr>
<tr class="memdesc:af98b404cae60bdcf0833ebaf35aae42c"><td class="mdescLeft">&#160;</td><td class="mdescRight">minimum number of points for a person cluster <br /></td></tr>
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<tr class="memitem:ae32f64895a5c1e5b03c33726ee4a4cad"><td class="memItemLeft" align="right" valign="top"><a id="ae32f64895a5c1e5b03c33726ee4a4cad"></a>
float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ae32f64895a5c1e5b03c33726ee4a4cad">heads_minimum_distance_</a></td></tr>
<tr class="memdesc:ae32f64895a5c1e5b03c33726ee4a4cad"><td class="mdescLeft">&#160;</td><td class="mdescRight">minimum distance between persons' heads <br /></td></tr>
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Eigen::Matrix3f&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ab784a9b530d0bc7b7903f2dbe050289a">intrinsics_matrix_</a></td></tr>
<tr class="memdesc:ab784a9b530d0bc7b7903f2dbe050289a"><td class="mdescLeft">&#160;</td><td class="mdescRight">intrinsic parameters matrix of the <a class="el" href="structpcl_1_1_r_g_b.html" title="A structure representing RGB color information.">RGB</a> camera <br /></td></tr>
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bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a49b28f258172678eb551be15c90ab67c">intrinsics_matrix_set_</a></td></tr>
<tr class="memdesc:a49b28f258172678eb551be15c90ab67c"><td class="mdescLeft">&#160;</td><td class="mdescRight">flag stating whether the intrinsics matrix has been set or not <br /></td></tr>
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Eigen::Matrix3f&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ab6a84ba87311742d10689f1c7497a1af">intrinsics_matrix_transformed_</a></td></tr>
<tr class="memdesc:ab6a84ba87311742d10689f1c7497a1af"><td class="mdescLeft">&#160;</td><td class="mdescRight">the transformed intrinsics matrix <br /></td></tr>
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<tr class="memitem:a1ecc9b5ce1a8116ffd77b256f1a7f272"><td class="memItemLeft" align="right" valign="top"><a id="a1ecc9b5ce1a8116ffd77b256f1a7f272"></a>
<a class="el" href="classpcl_1_1people_1_1_person_classifier.html">pcl::people::PersonClassifier</a>&lt; <a class="el" href="structpcl_1_1_r_g_b.html">pcl::RGB</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a1ecc9b5ce1a8116ffd77b256f1a7f272">person_classifier_</a></td></tr>
<tr class="memdesc:a1ecc9b5ce1a8116ffd77b256f1a7f272"><td class="mdescLeft">&#160;</td><td class="mdescRight">SVM-based person classifier <br /></td></tr>
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bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ac07fc1c8f970976e982d264de4e01854">person_classifier_set_flag_</a></td></tr>
<tr class="memdesc:ac07fc1c8f970976e982d264de4e01854"><td class="mdescLeft">&#160;</td><td class="mdescRight">flag stating if the classifier has been set or not <br /></td></tr>
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</table>
<a name="details" id="details"></a><h2 class="groupheader">详细描述</h2>
<div class="textblock"><h3>template&lt;typename PointT&gt;<br />
class pcl::people::GroundBasedPeopleDetectionApp&lt; PointT &gt;</h3>

<p><a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html" title="GroundBasedPeopleDetectionApp performs people detection on RGB-D data having as input the ground plan...">GroundBasedPeopleDetectionApp</a> performs people detection on RGB-D data having as input the ground plane coefficients. It implements the people detection algorithm described here: M. Munaro, F. Basso and E. Menegatti, Tracking people within groups with RGB-D data, In Proceedings of the International Conference on Intelligent Robots and Systems (IROS) 2012, Vilamoura (Portugal), 2012. </p>
<dl class="section author"><dt>作者</dt><dd>Matteo Munaro </dd></dl>
</div><h2 class="groupheader">成员函数说明</h2>
<a id="aef52be2a667ceb8c1c58b93c06125fa0"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aef52be2a667ceb8c1c58b93c06125fa0">&#9670;&nbsp;</a></span>compute()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">bool <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::compute </td>
          <td>(</td>
          <td class="paramtype">std::vector&lt; <a class="el" href="classpcl_1_1people_1_1_person_cluster.html">pcl::people::PersonCluster</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &gt; &amp;&#160;</td>
          <td class="paramname"><em>clusters</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Perform people detection on the input data and return people clusters information. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[out]</td><td class="paramname">clusters</td><td>Vector of <a class="el" href="classpcl_1_1people_1_1_person_cluster.html" title="PersonCluster represents a class for representing information about a cluster containing a person.">PersonCluster</a>.</td></tr>
  </table>
  </dd>
</dl>
<dl class="section return"><dt>返回</dt><dd>true if the compute operation is successful, false otherwise. </dd></dl>
<div class="fragment"><div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;{</div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;  <span class="comment">// Check if all mandatory variables have been set:</span></div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af2cab2d3c83b79a7004eec888fe37e57">ground_coeffs_set_</a>)</div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;  {</div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::people::GroundBasedPeopleDetectionApp::compute] Floor parameters have not been set or they are not valid!\n&quot;</span>);</div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;  }</div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;  <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a48d13a412a7e372b5a913bc861bd30ca">cloud_</a> == NULL)</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;  {</div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::people::GroundBasedPeopleDetectionApp::compute] Input cloud has not been set!\n&quot;</span>);</div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;  }</div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a49b28f258172678eb551be15c90ab67c">intrinsics_matrix_set_</a>)</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;  {</div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::people::GroundBasedPeopleDetectionApp::compute] Camera intrinsic parameters have not been set!\n&quot;</span>);</div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;  }</div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ac07fc1c8f970976e982d264de4e01854">person_classifier_set_flag_</a>)</div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;  {</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::people::GroundBasedPeopleDetectionApp::compute] Person classifier has not been set!\n&quot;</span>);</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;  }</div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160; </div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;  <span class="comment">// Fill rgb image:</span></div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af07013f8363c2b3d192f43e11ae7d4e6">rgb_image_</a>-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>.clear();                            <span class="comment">// clear RGB pointcloud</span></div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a1d2f9ad79adf98c4bfc5c156d97b12b8">extractRGBFromPointCloud</a>(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a48d13a412a7e372b5a913bc861bd30ca">cloud_</a>, <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af07013f8363c2b3d192f43e11ae7d4e6">rgb_image_</a>);          <span class="comment">// fill RGB pointcloud</span></div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160; </div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;  <span class="comment">// Downsample of sampling_factor in every dimension:</span></div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;  <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#afbf9a72fb4d539a13c14e49459a8a921">sampling_factor_</a> != 1)</div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;  {</div>
<div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;    PointCloudPtr cloud_downsampled(<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">PointCloud</a>);</div>
<div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;    cloud_downsampled-&gt;width = (<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a48d13a412a7e372b5a913bc861bd30ca">cloud_</a>-&gt;width)/<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#afbf9a72fb4d539a13c14e49459a8a921">sampling_factor_</a>;</div>
<div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;    cloud_downsampled-&gt;height = (<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a48d13a412a7e372b5a913bc861bd30ca">cloud_</a>-&gt;height)/<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#afbf9a72fb4d539a13c14e49459a8a921">sampling_factor_</a>;</div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;    cloud_downsampled-&gt;points.resize(cloud_downsampled-&gt;height*cloud_downsampled-&gt;width);</div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;    cloud_downsampled-&gt;is_dense = <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a48d13a412a7e372b5a913bc861bd30ca">cloud_</a>-&gt;is_dense;</div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;    <span class="keywordflow">for</span> (uint32_t j = 0; j &lt; cloud_downsampled-&gt;width; j++)</div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;    {</div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;      <span class="keywordflow">for</span> (uint32_t i = 0; i &lt; cloud_downsampled-&gt;height; i++)</div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;      {</div>
<div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;        (*cloud_downsampled)(j,i) = (*<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a48d13a412a7e372b5a913bc861bd30ca">cloud_</a>)(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#afbf9a72fb4d539a13c14e49459a8a921">sampling_factor_</a>*j,<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#afbf9a72fb4d539a13c14e49459a8a921">sampling_factor_</a>*i);</div>
<div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;      }</div>
<div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;    }</div>
<div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;    (*cloud_) = (*cloud_downsampled);</div>
<div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;  }</div>
<div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160; </div>
<div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a8aee7a6add005a4c42ade573585acfff">applyTransformationPointCloud</a>();</div>
<div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160; </div>
<div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a06ab91072245185aefb01e9f7c5f53bf">filter</a>();</div>
<div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160; </div>
<div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;  <span class="comment">// Ground removal and update:</span></div>
<div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;  pcl::IndicesPtr inliers(<span class="keyword">new</span> std::vector&lt;int&gt;);</div>
<div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;  boost::shared_ptr&lt;pcl::SampleConsensusModelPlane&lt;PointT&gt; &gt; ground_model(<span class="keyword">new</span> <a class="code" href="classpcl_1_1_sample_consensus_model_plane.html">pcl::SampleConsensusModelPlane&lt;PointT&gt;</a>(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a13d6dc63906ae29328565f5f42cf2a0d">cloud_filtered_</a>));</div>
<div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;  ground_model-&gt;selectWithinDistance(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aa6fce363d05279c79d9f441f731babd2">ground_coeffs_transformed_</a>, 2 * <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a9dfb9076a6111ff4588a554d83ef9971">voxel_size_</a>, *inliers);</div>
<div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a5cb6e71a2e30861f0a23804f432fed9a">no_ground_cloud_</a> = PointCloudPtr (<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">PointCloud</a>);</div>
<div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;  <a class="code" href="classpcl_1_1_extract_indices.html">pcl::ExtractIndices&lt;PointT&gt;</a> extract;</div>
<div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;  extract.<a class="code" href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">setInputCloud</a>(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a13d6dc63906ae29328565f5f42cf2a0d">cloud_filtered_</a>);</div>
<div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;  extract.<a class="code" href="classpcl_1_1_p_c_l_base.html#ab219359de6eb34c9d51e2e976dd1a0d1">setIndices</a>(inliers);</div>
<div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;  extract.<a class="code" href="classpcl_1_1_filter_indices.html#a8da0b86892188e59b0deb8d420a682bb">setNegative</a>(<span class="keyword">true</span>);</div>
<div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;  extract.filter(*<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a5cb6e71a2e30861f0a23804f432fed9a">no_ground_cloud_</a>);</div>
<div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;  <span class="keywordflow">if</span> (inliers-&gt;size () &gt;= (300 * 0.06 / <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a9dfb9076a6111ff4588a554d83ef9971">voxel_size_</a> / std::pow (<span class="keyword">static_cast&lt;</span><span class="keywordtype">double</span><span class="keyword">&gt;</span> (<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#afbf9a72fb4d539a13c14e49459a8a921">sampling_factor_</a>), 2)))</div>
<div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;    ground_model-&gt;optimizeModelCoefficients (*inliers, <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aa6fce363d05279c79d9f441f731babd2">ground_coeffs_transformed_</a>, <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aa6fce363d05279c79d9f441f731babd2">ground_coeffs_transformed_</a>);</div>
<div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;    PCL_INFO (<span class="stringliteral">&quot;No groundplane update!\n&quot;</span>);</div>
<div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160; </div>
<div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;  <span class="comment">// Euclidean Clustering:</span></div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;  std::vector&lt;pcl::PointIndices&gt; cluster_indices;</div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;  <span class="keyword">typename</span> pcl::search::KdTree&lt;PointT&gt;::Ptr tree (<span class="keyword">new</span> <a class="code" href="classpcl_1_1search_1_1_kd_tree.html">pcl::search::KdTree&lt;PointT&gt;</a>);</div>
<div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;  tree-&gt;setInputCloud(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a5cb6e71a2e30861f0a23804f432fed9a">no_ground_cloud_</a>);</div>
<div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;  <a class="code" href="classpcl_1_1_euclidean_cluster_extraction.html">pcl::EuclideanClusterExtraction&lt;PointT&gt;</a> ec;</div>
<div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;  ec.<a class="code" href="classpcl_1_1_euclidean_cluster_extraction.html#a8fb42fea2e8bfca4ebadf4339335cf11">setClusterTolerance</a>(2 * <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a9dfb9076a6111ff4588a554d83ef9971">voxel_size_</a>);</div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;  ec.<a class="code" href="classpcl_1_1_euclidean_cluster_extraction.html#a096af3508dd19b23a726a8323f7c7bba">setMinClusterSize</a>(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af98b404cae60bdcf0833ebaf35aae42c">min_points_</a>);</div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;  ec.<a class="code" href="classpcl_1_1_euclidean_cluster_extraction.html#adb0be906f101b309506cdc37ffd31624">setMaxClusterSize</a>(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aadfa9db61f00e6284608639649808cee">max_points_</a>);</div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;  ec.<a class="code" href="classpcl_1_1_euclidean_cluster_extraction.html#ac4162a11c1fd5797d507068a056bfbf7">setSearchMethod</a>(tree);</div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;  ec.<a class="code" href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">setInputCloud</a>(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a5cb6e71a2e30861f0a23804f432fed9a">no_ground_cloud_</a>);</div>
<div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;  ec.<a class="code" href="classpcl_1_1_euclidean_cluster_extraction.html#a41e0cd5e3f7967d59013c967c909585c">extract</a>(cluster_indices);</div>
<div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160; </div>
<div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;  <span class="comment">// Head based sub-clustering //</span></div>
<div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_head_based_subclustering.html">pcl::people::HeadBasedSubclustering&lt;PointT&gt;</a> subclustering;</div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;  subclustering.<a class="code" href="classpcl_1_1people_1_1_head_based_subclustering.html#ad140bf587d64742ccf80863a31420584">setInputCloud</a>(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a5cb6e71a2e30861f0a23804f432fed9a">no_ground_cloud_</a>);</div>
<div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;  subclustering.<a class="code" href="classpcl_1_1people_1_1_head_based_subclustering.html#a041e2143e796e359353c798f16f8be8d">setGround</a>(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aa6fce363d05279c79d9f441f731babd2">ground_coeffs_transformed_</a>);</div>
<div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;  subclustering.<a class="code" href="classpcl_1_1people_1_1_head_based_subclustering.html#a84a55359a8ff3af4b51d663a4c017f45">setInitialClusters</a>(cluster_indices);</div>
<div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;  subclustering.<a class="code" href="classpcl_1_1people_1_1_head_based_subclustering.html#abb32cbb48acaa44cd04ec25508e56ca9">setHeightLimits</a>(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ace264d669fdebef2ca84cf73c588ab50">min_height_</a>, <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af2574d41d6960ac7f44b7b988d2b1c21">max_height_</a>);</div>
<div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;  subclustering.<a class="code" href="classpcl_1_1people_1_1_head_based_subclustering.html#a866c04c3f4cd3c955a5217a4684ea36b">setMinimumDistanceBetweenHeads</a>(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ae32f64895a5c1e5b03c33726ee4a4cad">heads_minimum_distance_</a>);</div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;  subclustering.<a class="code" href="classpcl_1_1people_1_1_head_based_subclustering.html#aa397dfa3d093b2a9f86b3957513b9d94">setSensorPortraitOrientation</a>(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#afce08127bf56571649bc02755ec2b1b4">vertical_</a>);</div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;  subclustering.<a class="code" href="classpcl_1_1people_1_1_head_based_subclustering.html#a37e1d9543f43fc7c59fe3a795d01388e">subcluster</a>(clusters);</div>
<div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160; </div>
<div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;  <span class="comment">// Person confidence evaluation with HOG+SVM:</span></div>
<div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;  <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#afce08127bf56571649bc02755ec2b1b4">vertical_</a>)  <span class="comment">// Rotate the image if the camera is vertical</span></div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;  {</div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;    <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a60516702b769124ed3da3fd318258ba0">swapDimensions</a>(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af07013f8363c2b3d192f43e11ae7d4e6">rgb_image_</a>);</div>
<div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;  }</div>
<div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;  <span class="keywordflow">for</span>(<span class="keyword">typename</span> std::vector&lt;<a class="code" href="classpcl_1_1people_1_1_person_cluster.html">pcl::people::PersonCluster&lt;PointT&gt;</a> &gt;::iterator it = clusters.begin(); it != clusters.end(); ++it)</div>
<div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160;  {</div>
<div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;    <span class="comment">//Evaluate confidence for the current PersonCluster:</span></div>
<div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;    Eigen::Vector3f centroid = <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ab6a84ba87311742d10689f1c7497a1af">intrinsics_matrix_transformed_</a> * (it-&gt;getTCenter());</div>
<div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160;    centroid /= centroid(2);</div>
<div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;    Eigen::Vector3f top = <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ab6a84ba87311742d10689f1c7497a1af">intrinsics_matrix_transformed_</a> * (it-&gt;getTTop());</div>
<div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160;    top /= top(2);</div>
<div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;    Eigen::Vector3f bottom = <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ab6a84ba87311742d10689f1c7497a1af">intrinsics_matrix_transformed_</a> * (it-&gt;getTBottom());</div>
<div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;    bottom /= bottom(2);</div>
<div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;    it-&gt;setPersonConfidence(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a1ecc9b5ce1a8116ffd77b256f1a7f272">person_classifier_</a>.<a class="code" href="classpcl_1_1people_1_1_person_classifier.html#a4515d8e816f141408284bd25f74e916a">evaluate</a>(<a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af07013f8363c2b3d192f43e11ae7d4e6">rgb_image_</a>, bottom, top, centroid, <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#afce08127bf56571649bc02755ec2b1b4">vertical_</a>));</div>
<div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160;  }</div>
<div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160; </div>
<div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;  <span class="keywordflow">return</span> (<span class="keyword">true</span>);</div>
<div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1_euclidean_cluster_extraction_html"><div class="ttname"><a href="classpcl_1_1_euclidean_cluster_extraction.html">pcl::EuclideanClusterExtraction</a></div><div class="ttdoc">EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sen...</div><div class="ttdef"><b>Definition:</b> extract_clusters.h:296</div></div>
<div class="ttc" id="aclasspcl_1_1_euclidean_cluster_extraction_html_a096af3508dd19b23a726a8323f7c7bba"><div class="ttname"><a href="classpcl_1_1_euclidean_cluster_extraction.html#a096af3508dd19b23a726a8323f7c7bba">pcl::EuclideanClusterExtraction::setMinClusterSize</a></div><div class="ttdeci">void setMinClusterSize(int min_cluster_size)</div><div class="ttdoc">Set the minimum number of points that a cluster needs to contain in order to be considered valid.</div><div class="ttdef"><b>Definition:</b> extract_clusters.h:356</div></div>
<div class="ttc" id="aclasspcl_1_1_euclidean_cluster_extraction_html_a41e0cd5e3f7967d59013c967c909585c"><div class="ttname"><a href="classpcl_1_1_euclidean_cluster_extraction.html#a41e0cd5e3f7967d59013c967c909585c">pcl::EuclideanClusterExtraction::extract</a></div><div class="ttdeci">void extract(std::vector&lt; PointIndices &gt; &amp;clusters)</div><div class="ttdoc">Cluster extraction in a PointCloud given by &lt;setInputCloud (), setIndices ()&gt;</div><div class="ttdef"><b>Definition:</b> extract_clusters.hpp:210</div></div>
<div class="ttc" id="aclasspcl_1_1_euclidean_cluster_extraction_html_a8fb42fea2e8bfca4ebadf4339335cf11"><div class="ttname"><a href="classpcl_1_1_euclidean_cluster_extraction.html#a8fb42fea2e8bfca4ebadf4339335cf11">pcl::EuclideanClusterExtraction::setClusterTolerance</a></div><div class="ttdeci">void setClusterTolerance(double tolerance)</div><div class="ttdoc">Set the spatial cluster tolerance as a measure in the L2 Euclidean space</div><div class="ttdef"><b>Definition:</b> extract_clusters.h:340</div></div>
<div class="ttc" id="aclasspcl_1_1_euclidean_cluster_extraction_html_ac4162a11c1fd5797d507068a056bfbf7"><div class="ttname"><a href="classpcl_1_1_euclidean_cluster_extraction.html#ac4162a11c1fd5797d507068a056bfbf7">pcl::EuclideanClusterExtraction::setSearchMethod</a></div><div class="ttdeci">void setSearchMethod(const KdTreePtr &amp;tree)</div><div class="ttdoc">Provide a pointer to the search object.</div><div class="ttdef"><b>Definition:</b> extract_clusters.h:322</div></div>
<div class="ttc" id="aclasspcl_1_1_euclidean_cluster_extraction_html_adb0be906f101b309506cdc37ffd31624"><div class="ttname"><a href="classpcl_1_1_euclidean_cluster_extraction.html#adb0be906f101b309506cdc37ffd31624">pcl::EuclideanClusterExtraction::setMaxClusterSize</a></div><div class="ttdeci">void setMaxClusterSize(int max_cluster_size)</div><div class="ttdoc">Set the maximum number of points that a cluster needs to contain in order to be considered valid.</div><div class="ttdef"><b>Definition:</b> extract_clusters.h:372</div></div>
<div class="ttc" id="aclasspcl_1_1_extract_indices_html"><div class="ttname"><a href="classpcl_1_1_extract_indices.html">pcl::ExtractIndices</a></div><div class="ttdoc">ExtractIndices extracts a set of indices from a point cloud.</div><div class="ttdef"><b>Definition:</b> extract_indices.h:71</div></div>
<div class="ttc" id="aclasspcl_1_1_filter_indices_html_a8da0b86892188e59b0deb8d420a682bb"><div class="ttname"><a href="classpcl_1_1_filter_indices.html#a8da0b86892188e59b0deb8d420a682bb">pcl::FilterIndices::setNegative</a></div><div class="ttdeci">void setNegative(bool negative)</div><div class="ttdoc">Set whether the regular conditions for points filtering should apply, or the inverted conditions.</div><div class="ttdef"><b>Definition:</b> filter_indices.h:127</div></div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_base_html_a1952d7101f3942bac3b69ed55c1ca7ea"><div class="ttname"><a href="classpcl_1_1_p_c_l_base.html#a1952d7101f3942bac3b69ed55c1ca7ea">pcl::PCLBase::setInputCloud</a></div><div class="ttdeci">virtual void setInputCloud(const PointCloudConstPtr &amp;cloud)</div><div class="ttdoc">Provide a pointer to the input dataset</div><div class="ttdef"><b>Definition:</b> pcl_base.hpp:66</div></div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_base_html_ab219359de6eb34c9d51e2e976dd1a0d1"><div class="ttname"><a href="classpcl_1_1_p_c_l_base.html#ab219359de6eb34c9d51e2e976dd1a0d1">pcl::PCLBase::setIndices</a></div><div class="ttdeci">virtual void setIndices(const IndicesPtr &amp;indices)</div><div class="ttdoc">Provide a pointer to the vector of indices that represents the input data.</div><div class="ttdef"><b>Definition:</b> pcl_base.hpp:73</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html"><div class="ttname"><a href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a></div><div class="ttdoc">PointCloud represents the base class in PCL for storing collections of 3D points.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:173</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_af16a62638198313b9c093127c492c884"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">pcl::PointCloud::points</a></div><div class="ttdeci">std::vector&lt; PointT, Eigen::aligned_allocator&lt; PointT &gt; &gt; points</div><div class="ttdoc">The point data.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:410</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_plane_html"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model_plane.html">pcl::SampleConsensusModelPlane</a></div><div class="ttdoc">SampleConsensusModelPlane defines a model for 3D plane segmentation. The model coefficients are defin...</div><div class="ttdef"><b>Definition:</b> sac_model_plane.h:137</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a06ab91072245185aefb01e9f7c5f53bf"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a06ab91072245185aefb01e9f7c5f53bf">pcl::people::GroundBasedPeopleDetectionApp::filter</a></div><div class="ttdeci">void filter()</div><div class="ttdoc">Reduces the input cloud to one point per voxel and limits the field of view.</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.hpp:296</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a13d6dc63906ae29328565f5f42cf2a0d"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a13d6dc63906ae29328565f5f42cf2a0d">pcl::people::GroundBasedPeopleDetectionApp::cloud_filtered_</a></div><div class="ttdeci">PointCloudPtr cloud_filtered_</div><div class="ttdoc">pointer to the filtered cloud</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:315</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a1d2f9ad79adf98c4bfc5c156d97b12b8"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a1d2f9ad79adf98c4bfc5c156d97b12b8">pcl::people::GroundBasedPeopleDetectionApp::extractRGBFromPointCloud</a></div><div class="ttdeci">void extractRGBFromPointCloud(PointCloudPtr input_cloud, pcl::PointCloud&lt; pcl::RGB &gt;::Ptr &amp;output_cloud)</div><div class="ttdoc">Extract RGB information from a point cloud and output the corresponding RGB point cloud.</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.hpp:219</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a1ecc9b5ce1a8116ffd77b256f1a7f272"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a1ecc9b5ce1a8116ffd77b256f1a7f272">pcl::people::GroundBasedPeopleDetectionApp::person_classifier_</a></div><div class="ttdeci">pcl::people::PersonClassifier&lt; pcl::RGB &gt; person_classifier_</div><div class="ttdoc">SVM-based person classifier</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:367</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a48d13a412a7e372b5a913bc861bd30ca"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a48d13a412a7e372b5a913bc861bd30ca">pcl::people::GroundBasedPeopleDetectionApp::cloud_</a></div><div class="ttdeci">PointCloudPtr cloud_</div><div class="ttdoc">pointer to the input cloud</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:312</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a49b28f258172678eb551be15c90ab67c"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a49b28f258172678eb551be15c90ab67c">pcl::people::GroundBasedPeopleDetectionApp::intrinsics_matrix_set_</a></div><div class="ttdeci">bool intrinsics_matrix_set_</div><div class="ttdoc">flag stating whether the intrinsics matrix has been set or not</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:361</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a5cb6e71a2e30861f0a23804f432fed9a"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a5cb6e71a2e30861f0a23804f432fed9a">pcl::people::GroundBasedPeopleDetectionApp::no_ground_cloud_</a></div><div class="ttdeci">PointCloudPtr no_ground_cloud_</div><div class="ttdoc">pointer to the cloud after voxel grid filtering and ground removal</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:318</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a60516702b769124ed3da3fd318258ba0"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a60516702b769124ed3da3fd318258ba0">pcl::people::GroundBasedPeopleDetectionApp::swapDimensions</a></div><div class="ttdeci">void swapDimensions(pcl::PointCloud&lt; pcl::RGB &gt;::Ptr &amp;cloud)</div><div class="ttdoc">Swap rows/cols dimensions of a RGB point cloud (90 degrees counterclockwise rotation).</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.hpp:240</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a8aee7a6add005a4c42ade573585acfff"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a8aee7a6add005a4c42ade573585acfff">pcl::people::GroundBasedPeopleDetectionApp::applyTransformationPointCloud</a></div><div class="ttdeci">void applyTransformationPointCloud()</div><div class="ttdoc">Applies the transformation to the input point cloud.</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.hpp:257</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a9dfb9076a6111ff4588a554d83ef9971"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a9dfb9076a6111ff4588a554d83ef9971">pcl::people::GroundBasedPeopleDetectionApp::voxel_size_</a></div><div class="ttdeci">float voxel_size_</div><div class="ttdoc">voxel size</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:291</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_aa6fce363d05279c79d9f441f731babd2"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aa6fce363d05279c79d9f441f731babd2">pcl::people::GroundBasedPeopleDetectionApp::ground_coeffs_transformed_</a></div><div class="ttdeci">Eigen::VectorXf ground_coeffs_transformed_</div><div class="ttdoc">the transformed ground coefficients</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:300</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_aadfa9db61f00e6284608639649808cee"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aadfa9db61f00e6284608639649808cee">pcl::people::GroundBasedPeopleDetectionApp::max_points_</a></div><div class="ttdeci">int max_points_</div><div class="ttdoc">maximum number of points for a person cluster</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:349</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_ab6a84ba87311742d10689f1c7497a1af"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ab6a84ba87311742d10689f1c7497a1af">pcl::people::GroundBasedPeopleDetectionApp::intrinsics_matrix_transformed_</a></div><div class="ttdeci">Eigen::Matrix3f intrinsics_matrix_transformed_</div><div class="ttdoc">the transformed intrinsics matrix</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:364</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_ac07fc1c8f970976e982d264de4e01854"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ac07fc1c8f970976e982d264de4e01854">pcl::people::GroundBasedPeopleDetectionApp::person_classifier_set_flag_</a></div><div class="ttdeci">bool person_classifier_set_flag_</div><div class="ttdoc">flag stating if the classifier has been set or not</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:370</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_ace264d669fdebef2ca84cf73c588ab50"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ace264d669fdebef2ca84cf73c588ab50">pcl::people::GroundBasedPeopleDetectionApp::min_height_</a></div><div class="ttdeci">float min_height_</div><div class="ttdoc">person clusters minimum height from the ground plane</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:327</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_ae32f64895a5c1e5b03c33726ee4a4cad"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ae32f64895a5c1e5b03c33726ee4a4cad">pcl::people::GroundBasedPeopleDetectionApp::heads_minimum_distance_</a></div><div class="ttdeci">float heads_minimum_distance_</div><div class="ttdoc">minimum distance between persons' heads</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:355</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_af07013f8363c2b3d192f43e11ae7d4e6"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af07013f8363c2b3d192f43e11ae7d4e6">pcl::people::GroundBasedPeopleDetectionApp::rgb_image_</a></div><div class="ttdeci">pcl::PointCloud&lt; pcl::RGB &gt;::Ptr rgb_image_</div><div class="ttdoc">pointer to a RGB cloud corresponding to cloud_</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:321</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_af2574d41d6960ac7f44b7b988d2b1c21"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af2574d41d6960ac7f44b7b988d2b1c21">pcl::people::GroundBasedPeopleDetectionApp::max_height_</a></div><div class="ttdeci">float max_height_</div><div class="ttdoc">person clusters maximum height from the ground plane</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:324</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_af2cab2d3c83b79a7004eec888fe37e57"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af2cab2d3c83b79a7004eec888fe37e57">pcl::people::GroundBasedPeopleDetectionApp::ground_coeffs_set_</a></div><div class="ttdeci">bool ground_coeffs_set_</div><div class="ttdoc">flag stating whether the ground coefficients have been set or not</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:297</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_af98b404cae60bdcf0833ebaf35aae42c"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af98b404cae60bdcf0833ebaf35aae42c">pcl::people::GroundBasedPeopleDetectionApp::min_points_</a></div><div class="ttdeci">int min_points_</div><div class="ttdoc">minimum number of points for a person cluster</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:352</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_afbf9a72fb4d539a13c14e49459a8a921"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#afbf9a72fb4d539a13c14e49459a8a921">pcl::people::GroundBasedPeopleDetectionApp::sampling_factor_</a></div><div class="ttdeci">int sampling_factor_</div><div class="ttdoc">sampling factor used to downsample the point cloud</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:288</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_afce08127bf56571649bc02755ec2b1b4"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#afce08127bf56571649bc02755ec2b1b4">pcl::people::GroundBasedPeopleDetectionApp::vertical_</a></div><div class="ttdeci">bool vertical_</div><div class="ttdoc">if true, the sensor is considered to be vertically placed (portrait mode)</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:342</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_head_based_subclustering_html"><div class="ttname"><a href="classpcl_1_1people_1_1_head_based_subclustering.html">pcl::people::HeadBasedSubclustering</a></div><div class="ttdoc">HeadBasedSubclustering represents a class for searching for people inside a HeightMap2D based on a 3D...</div><div class="ttdef"><b>Definition:</b> head_based_subcluster.h:60</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_head_based_subclustering_html_a041e2143e796e359353c798f16f8be8d"><div class="ttname"><a href="classpcl_1_1people_1_1_head_based_subclustering.html#a041e2143e796e359353c798f16f8be8d">pcl::people::HeadBasedSubclustering::setGround</a></div><div class="ttdeci">void setGround(Eigen::VectorXf &amp;ground_coeffs)</div><div class="ttdoc">Set the ground coefficients.</div><div class="ttdef"><b>Definition:</b> head_based_subcluster.hpp:69</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_head_based_subclustering_html_a37e1d9543f43fc7c59fe3a795d01388e"><div class="ttname"><a href="classpcl_1_1people_1_1_head_based_subclustering.html#a37e1d9543f43fc7c59fe3a795d01388e">pcl::people::HeadBasedSubclustering::subcluster</a></div><div class="ttdeci">void subcluster(std::vector&lt; pcl::people::PersonCluster&lt; PointT &gt; &gt; &amp;clusters)</div><div class="ttdoc">Compute subclusters and return them into a vector of PersonCluster.</div><div class="ttdef"><b>Definition:</b> head_based_subcluster.hpp:255</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_head_based_subclustering_html_a84a55359a8ff3af4b51d663a4c017f45"><div class="ttname"><a href="classpcl_1_1people_1_1_head_based_subclustering.html#a84a55359a8ff3af4b51d663a4c017f45">pcl::people::HeadBasedSubclustering::setInitialClusters</a></div><div class="ttdeci">void setInitialClusters(std::vector&lt; pcl::PointIndices &gt; &amp;cluster_indices)</div><div class="ttdoc">Set initial cluster indices.</div><div class="ttdef"><b>Definition:</b> head_based_subcluster.hpp:76</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_head_based_subclustering_html_a866c04c3f4cd3c955a5217a4684ea36b"><div class="ttname"><a href="classpcl_1_1people_1_1_head_based_subclustering.html#a866c04c3f4cd3c955a5217a4684ea36b">pcl::people::HeadBasedSubclustering::setMinimumDistanceBetweenHeads</a></div><div class="ttdeci">void setMinimumDistanceBetweenHeads(float heads_minimum_distance)</div><div class="ttdoc">Set minimum distance between persons' heads.</div><div class="ttdef"><b>Definition:</b> head_based_subcluster.hpp:102</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_head_based_subclustering_html_aa397dfa3d093b2a9f86b3957513b9d94"><div class="ttname"><a href="classpcl_1_1people_1_1_head_based_subclustering.html#aa397dfa3d093b2a9f86b3957513b9d94">pcl::people::HeadBasedSubclustering::setSensorPortraitOrientation</a></div><div class="ttdeci">void setSensorPortraitOrientation(bool vertical)</div><div class="ttdoc">Set sensor orientation to landscape mode (false) or portrait mode (true).</div><div class="ttdef"><b>Definition:</b> head_based_subcluster.hpp:82</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_head_based_subclustering_html_abb32cbb48acaa44cd04ec25508e56ca9"><div class="ttname"><a href="classpcl_1_1people_1_1_head_based_subclustering.html#abb32cbb48acaa44cd04ec25508e56ca9">pcl::people::HeadBasedSubclustering::setHeightLimits</a></div><div class="ttdeci">void setHeightLimits(float min_height, float max_height)</div><div class="ttdoc">Set minimum and maximum allowed height for a person cluster.</div><div class="ttdef"><b>Definition:</b> head_based_subcluster.hpp:88</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_head_based_subclustering_html_ad140bf587d64742ccf80863a31420584"><div class="ttname"><a href="classpcl_1_1people_1_1_head_based_subclustering.html#ad140bf587d64742ccf80863a31420584">pcl::people::HeadBasedSubclustering::setInputCloud</a></div><div class="ttdeci">void setInputCloud(PointCloudPtr &amp;cloud)</div><div class="ttdoc">Set input cloud.</div><div class="ttdef"><b>Definition:</b> head_based_subcluster.hpp:63</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_person_classifier_html_a4515d8e816f141408284bd25f74e916a"><div class="ttname"><a href="classpcl_1_1people_1_1_person_classifier.html#a4515d8e816f141408284bd25f74e916a">pcl::people::PersonClassifier::evaluate</a></div><div class="ttdeci">double evaluate(float height, float xc, float yc, PointCloudPtr &amp;image)</div><div class="ttdoc">Classify the given portion of image.</div><div class="ttdef"><b>Definition:</b> person_classifier.hpp:216</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_person_cluster_html"><div class="ttname"><a href="classpcl_1_1people_1_1_person_cluster.html">pcl::people::PersonCluster</a></div><div class="ttdoc">PersonCluster represents a class for representing information about a cluster containing a person.</div><div class="ttdef"><b>Definition:</b> person_cluster.h:60</div></div>
<div class="ttc" id="aclasspcl_1_1search_1_1_kd_tree_html"><div class="ttname"><a href="classpcl_1_1search_1_1_kd_tree.html">pcl::search::KdTree</a></div><div class="ttdoc">search::KdTree is a wrapper class which inherits the pcl::KdTree class for performing search function...</div><div class="ttdef"><b>Definition:</b> kdtree.h:63</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a1d2f9ad79adf98c4bfc5c156d97b12b8">&#9670;&nbsp;</a></span>extractRGBFromPointCloud()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::extractRGBFromPointCloud </td>
          <td>(</td>
          <td class="paramtype">PointCloudPtr&#160;</td>
          <td class="paramname"><em>input_cloud</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_r_g_b.html">pcl::RGB</a> &gt;::Ptr &amp;&#160;</td>
          <td class="paramname"><em>output_cloud</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
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<p>Extract <a class="el" href="structpcl_1_1_r_g_b.html" title="A structure representing RGB color information.">RGB</a> information from a point cloud and output the corresponding <a class="el" href="structpcl_1_1_r_g_b.html" title="A structure representing RGB color information.">RGB</a> point cloud. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">input_cloud</td><td>A pointer to a point cloud containing also <a class="el" href="structpcl_1_1_r_g_b.html" title="A structure representing RGB color information.">RGB</a> information. </td></tr>
    <tr><td class="paramdir">[out]</td><td class="paramname">output_cloud</td><td>A pointer to a <a class="el" href="structpcl_1_1_r_g_b.html" title="A structure representing RGB color information.">RGB</a> point cloud. </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;{</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;  <span class="comment">// Extract RGB information from a point cloud and output the corresponding RGB point cloud  </span></div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;  output_cloud-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>.resize(input_cloud-&gt;height*input_cloud-&gt;width);</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;  output_cloud-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#a2185a6453f8ad905d7bdf7b45754a160">width</a> = input_cloud-&gt;width;</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;  output_cloud-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#a4f34b45220c57f96607513ffad0d9582">height</a> = input_cloud-&gt;height;</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160; </div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;  <a class="code" href="structpcl_1_1_r_g_b.html">pcl::RGB</a> rgb_point;</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;  <span class="keywordflow">for</span> (uint32_t j = 0; j &lt; input_cloud-&gt;width; j++)</div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;  {</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;    <span class="keywordflow">for</span> (uint32_t i = 0; i &lt; input_cloud-&gt;height; i++)</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;    { </div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;      rgb_point.r = (*input_cloud)(j,i).r;</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;      rgb_point.g = (*input_cloud)(j,i).g;</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;      rgb_point.b = (*input_cloud)(j,i).b;    </div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;      (*output_cloud)(j,i) = rgb_point; </div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;    }</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;  }</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_a2185a6453f8ad905d7bdf7b45754a160"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#a2185a6453f8ad905d7bdf7b45754a160">pcl::PointCloud::width</a></div><div class="ttdeci">uint32_t width</div><div class="ttdoc">The point cloud width (if organized as an image-structure).</div><div class="ttdef"><b>Definition:</b> point_cloud.h:413</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_a4f34b45220c57f96607513ffad0d9582"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#a4f34b45220c57f96607513ffad0d9582">pcl::PointCloud::height</a></div><div class="ttdeci">uint32_t height</div><div class="ttdoc">The point cloud height (if organized as an image-structure).</div><div class="ttdef"><b>Definition:</b> point_cloud.h:415</div></div>
<div class="ttc" id="astructpcl_1_1_r_g_b_html"><div class="ttname"><a href="structpcl_1_1_r_g_b.html">pcl::RGB</a></div><div class="ttdoc">A structure representing RGB color information.</div><div class="ttdef"><b>Definition:</b> point_types.hpp:334</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a00e3e22879cc58458e8bc1d57f1f0b4c">&#9670;&nbsp;</a></span>getDimensionLimits()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::getDimensionLimits </td>
          <td>(</td>
          <td class="paramtype">int &amp;&#160;</td>
          <td class="paramname"><em>min_points</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int &amp;&#160;</td>
          <td class="paramname"><em>max_points</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Get minimum and maximum allowed number of points for a person cluster. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[out]</td><td class="paramname">min_points</td><td>Minimum allowed number of points for a person cluster. </td></tr>
    <tr><td class="paramdir">[out]</td><td class="paramname">max_points</td><td>Maximum allowed number of points for a person cluster. </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;{</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;  min_points = <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af98b404cae60bdcf0833ebaf35aae42c">min_points_</a>;</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;  max_points = <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aadfa9db61f00e6284608639649808cee">max_points_</a>;</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;}</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a96dd362f2971dab29b62c02ebf0a4ad2">&#9670;&nbsp;</a></span>getPersonClusterLimits()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::getPersonClusterLimits </td>
          <td>(</td>
          <td class="paramtype">float &amp;&#160;</td>
          <td class="paramname"><em>min_height</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float &amp;&#160;</td>
          <td class="paramname"><em>max_height</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float &amp;&#160;</td>
          <td class="paramname"><em>min_width</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float &amp;&#160;</td>
          <td class="paramname"><em>max_width</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Get the minimum and maximum allowed height and width for a person cluster. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[out]</td><td class="paramname">min_height</td><td>Minimum allowed height for a person cluster. </td></tr>
    <tr><td class="paramdir">[out]</td><td class="paramname">max_height</td><td>Maximum allowed height for a person cluster. </td></tr>
    <tr><td class="paramdir">[out]</td><td class="paramname">min_width</td><td>Minimum width for a person cluster. </td></tr>
    <tr><td class="paramdir">[out]</td><td class="paramname">max_width</td><td>Maximum width for a person cluster. </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;{</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;  min_height = <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ace264d669fdebef2ca84cf73c588ab50">min_height_</a>;</div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;  max_height = <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af2574d41d6960ac7f44b7b988d2b1c21">max_height_</a>;</div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;  min_width = <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a07e0d9ca813b18b185606309ee11a7f9">min_width_</a>;</div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;  max_width = <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a5db06c5ec4b26cdf2f7658fb347082f9">max_width_</a>;</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a07e0d9ca813b18b185606309ee11a7f9"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a07e0d9ca813b18b185606309ee11a7f9">pcl::people::GroundBasedPeopleDetectionApp::min_width_</a></div><div class="ttdeci">float min_width_</div><div class="ttdoc">person clusters minimum width, used to estimate how many points minimally represent a person cluster</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:333</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a5db06c5ec4b26cdf2f7658fb347082f9"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a5db06c5ec4b26cdf2f7658fb347082f9">pcl::people::GroundBasedPeopleDetectionApp::max_width_</a></div><div class="ttdeci">float max_width_</div><div class="ttdoc">person clusters maximum width, used to estimate how many points maximally represent a person cluster</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:330</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a31940f8ad83752c91fed13ef030bf714">&#9670;&nbsp;</a></span>setClassifier()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setClassifier </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="classpcl_1_1people_1_1_person_classifier.html">pcl::people::PersonClassifier</a>&lt; <a class="el" href="structpcl_1_1_r_g_b.html">pcl::RGB</a> &gt;&#160;</td>
          <td class="paramname"><em>person_classifier</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Set SVM-based person classifier. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">person_classifier</td><td>Needed for people detection on <a class="el" href="structpcl_1_1_r_g_b.html" title="A structure representing RGB color information.">RGB</a> data. </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;{</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a1ecc9b5ce1a8116ffd77b256f1a7f272">person_classifier_</a> = person_classifier;</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ac07fc1c8f970976e982d264de4e01854">person_classifier_set_flag_</a> = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;}</div>
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<h2 class="memtitle"><span class="permalink"><a href="#aa863e592db0f6d0e943f11a1ee93b564">&#9670;&nbsp;</a></span>setFOV()</h2>

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<div class="memtemplate">
template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setFOV </td>
          <td>(</td>
          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>min</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>max</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Set the field of view of the point cloud in z direction. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">min</td><td>The beginning of the field of view in z-direction, should be usually set to zero. </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">max</td><td>The end of the field of view in z-direction. </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;{</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a2f9749e800d83673bcc5f5d7f2643626">min_fov_</a> = min_fov;</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a50fe9985ffec0898fcdf2863eb620f29">max_fov_</a> = max_fov;</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a2f9749e800d83673bcc5f5d7f2643626"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a2f9749e800d83673bcc5f5d7f2643626">pcl::people::GroundBasedPeopleDetectionApp::min_fov_</a></div><div class="ttdeci">float min_fov_</div><div class="ttdoc">the beginning of the field of view in z-direction, should be usually set to zero</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:336</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a50fe9985ffec0898fcdf2863eb620f29"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a50fe9985ffec0898fcdf2863eb620f29">pcl::people::GroundBasedPeopleDetectionApp::max_fov_</a></div><div class="ttdeci">float max_fov_</div><div class="ttdoc">the end of the field of view in z-direction</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:339</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a6ad2ce897659e25fd5552be5cfcebd50">&#9670;&nbsp;</a></span>setGround()</h2>

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<div class="memtemplate">
template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setGround </td>
          <td>(</td>
          <td class="paramtype">Eigen::VectorXf &amp;&#160;</td>
          <td class="paramname"><em>ground_coeffs</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Set the ground coefficients. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">ground_coeffs</td><td>Vector containing the four plane coefficients. </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;{</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aa72a39059ffc190840f21eff697fb40f">ground_coeffs_</a> = ground_coeffs;</div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af2cab2d3c83b79a7004eec888fe37e57">ground_coeffs_set_</a> = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a995fba929fa9febd580581fe143a3521">sqrt_ground_coeffs_</a> = (ground_coeffs - Eigen::Vector4f(0.0f, 0.0f, 0.0f, ground_coeffs(3))).norm();</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ad88876b8e9f69b703ffc26d1d5c92760">applyTransformationGround</a>();</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a995fba929fa9febd580581fe143a3521"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a995fba929fa9febd580581fe143a3521">pcl::people::GroundBasedPeopleDetectionApp::sqrt_ground_coeffs_</a></div><div class="ttdeci">float sqrt_ground_coeffs_</div><div class="ttdoc">ground plane normalization factor</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:303</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_aa72a39059ffc190840f21eff697fb40f"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#aa72a39059ffc190840f21eff697fb40f">pcl::people::GroundBasedPeopleDetectionApp::ground_coeffs_</a></div><div class="ttdeci">Eigen::VectorXf ground_coeffs_</div><div class="ttdoc">ground plane coefficients</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:294</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_ad88876b8e9f69b703ffc26d1d5c92760"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ad88876b8e9f69b703ffc26d1d5c92760">pcl::people::GroundBasedPeopleDetectionApp::applyTransformationGround</a></div><div class="ttdeci">void applyTransformationGround()</div><div class="ttdoc">Applies the transformation to the ground plane.</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.hpp:268</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a31b917712ffe4f66d8ecf85ee9e71749">&#9670;&nbsp;</a></span>setHeadCentroid()</h2>

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<div class="memtemplate">
template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setHeadCentroid </td>
          <td>(</td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>head_centroid</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Set head_centroid_ to true (person centroid is in the head) or false (person centroid is the whole body centroid). </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">head_centroid</td><td>Set the location of the person centroid (head or body center) (default = true). </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;{</div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af72e2f00dace33c58439512a731749f6">head_centroid_</a> = head_centroid;</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_af72e2f00dace33c58439512a731749f6"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af72e2f00dace33c58439512a731749f6">pcl::people::GroundBasedPeopleDetectionApp::head_centroid_</a></div><div class="ttdeci">bool head_centroid_</div><div class="ttdoc">if true, the person centroid is computed as the centroid of the cluster points belonging to the head;...</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:346</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a4d891de9e757b98155a630ac7a7c9de7">&#9670;&nbsp;</a></span>setInputCloud()</h2>

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<div class="memproto">
<div class="memtemplate">
template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setInputCloud </td>
          <td>(</td>
          <td class="paramtype">PointCloudPtr &amp;&#160;</td>
          <td class="paramname"><em>cloud</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Set the pointer to the input cloud. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">cloud</td><td>A pointer to the input cloud. </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;{</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a48d13a412a7e372b5a913bc861bd30ca">cloud_</a> = cloud;</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;}</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a915f68c8aa39a15fc5a129a6d87b00a5">&#9670;&nbsp;</a></span>setIntrinsics()</h2>

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<div class="memtemplate">
template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setIntrinsics </td>
          <td>(</td>
          <td class="paramtype">Eigen::Matrix3f&#160;</td>
          <td class="paramname"><em>intrinsics_matrix</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Set intrinsic parameters of the <a class="el" href="structpcl_1_1_r_g_b.html" title="A structure representing RGB color information.">RGB</a> camera. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">intrinsics_matrix</td><td><a class="el" href="structpcl_1_1_r_g_b.html" title="A structure representing RGB color information.">RGB</a> camera intrinsic parameters matrix. </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;{</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ab784a9b530d0bc7b7903f2dbe050289a">intrinsics_matrix_</a> = intrinsics_matrix;</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a49b28f258172678eb551be15c90ab67c">intrinsics_matrix_set_</a> = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a0dc924992669bcd76b7dad68cfd5c5f6">applyTransformationIntrinsics</a>();</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a0dc924992669bcd76b7dad68cfd5c5f6"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a0dc924992669bcd76b7dad68cfd5c5f6">pcl::people::GroundBasedPeopleDetectionApp::applyTransformationIntrinsics</a></div><div class="ttdeci">void applyTransformationIntrinsics()</div><div class="ttdoc">Applies the transformation to the intrinsics matrix.</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.hpp:283</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_ab784a9b530d0bc7b7903f2dbe050289a"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ab784a9b530d0bc7b7903f2dbe050289a">pcl::people::GroundBasedPeopleDetectionApp::intrinsics_matrix_</a></div><div class="ttdeci">Eigen::Matrix3f intrinsics_matrix_</div><div class="ttdoc">intrinsic parameters matrix of the RGB camera</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:358</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a2c906736068e8325c05243de6460dba4">&#9670;&nbsp;</a></span>setMinimumDistanceBetweenHeads()</h2>

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template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setMinimumDistanceBetweenHeads </td>
          <td>(</td>
          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>heads_minimum_distance</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Set minimum distance between persons' heads. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">heads_minimum_distance</td><td>Minimum allowed distance between persons' heads (default = 0.3). </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;{</div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ae32f64895a5c1e5b03c33726ee4a4cad">heads_minimum_distance_</a>= heads_minimum_distance;</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;}</div>
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<h2 class="memtitle"><span class="permalink"><a href="#ab089c9fe913edf8b5aff9d9e64f6914a">&#9670;&nbsp;</a></span>setPersonClusterLimits()</h2>

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<div class="memtemplate">
template&lt;typename PointT &gt; </div>
      <table class="memname">
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          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setPersonClusterLimits </td>
          <td>(</td>
          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>min_height</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>max_height</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>min_width</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>max_width</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Set minimum and maximum allowed height and width for a person cluster. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">min_height</td><td>Minimum allowed height for a person cluster (default = 1.3). </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">max_height</td><td>Maximum allowed height for a person cluster (default = 2.3). </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">min_width</td><td>Minimum width for a person cluster (default = 0.1). </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">max_width</td><td>Maximum width for a person cluster (default = 8.0). </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;{</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ace264d669fdebef2ca84cf73c588ab50">min_height_</a> = min_height;</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#af2574d41d6960ac7f44b7b988d2b1c21">max_height_</a> = max_height;</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a07e0d9ca813b18b185606309ee11a7f9">min_width_</a> = min_width;</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a5db06c5ec4b26cdf2f7658fb347082f9">max_width_</a> = max_width;</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a74d6d3cb5fd914ed35b0d23702719912">updateMinMaxPoints</a> ();</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a74d6d3cb5fd914ed35b0d23702719912"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a74d6d3cb5fd914ed35b0d23702719912">pcl::people::GroundBasedPeopleDetectionApp::updateMinMaxPoints</a></div><div class="ttdeci">void updateMinMaxPoints()</div><div class="ttdoc">Estimates min_points_ and max_points_ based on the minimal and maximal cluster size and the voxel siz...</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.hpp:146</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a19a15f63fc6648a65d54e2d70e6dbd7e">&#9670;&nbsp;</a></span>setSamplingFactor()</h2>

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template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setSamplingFactor </td>
          <td>(</td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>sampling_factor</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Set sampling factor. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">sampling_factor</td><td>Value of the downsampling factor (in each dimension) which is applied to the raw point cloud (default = 1.). </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;{</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#afbf9a72fb4d539a13c14e49459a8a921">sampling_factor_</a> = sampling_factor;</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;}</div>
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<h2 class="memtitle"><span class="permalink"><a href="#af5662950e81c30873915ed91dcc0d0d2">&#9670;&nbsp;</a></span>setSensorPortraitOrientation()</h2>

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template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setSensorPortraitOrientation </td>
          <td>(</td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>vertical</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Set sensor orientation (vertical = true means portrait mode, vertical = false means landscape mode). </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">vertical</td><td>Set landscape/portait camera orientation (default = false). </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;{</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#afce08127bf56571649bc02755ec2b1b4">vertical_</a> = vertical;</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;}</div>
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<h2 class="memtitle"><span class="permalink"><a href="#abb1e96641bf0cd5d87ec9d32181a3efa">&#9670;&nbsp;</a></span>setTransformation()</h2>

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<div class="memtemplate">
template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setTransformation </td>
          <td>(</td>
          <td class="paramtype">const Eigen::Matrix3f &amp;&#160;</td>
          <td class="paramname"><em>transformation</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Set the transformation matrix, which is used in order to transform the given point cloud, the ground plane and the intrinsics matrix to the internal coordinate frame. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">transformation</td><td></td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;{</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;  <span class="keywordflow">if</span> (!transformation.isUnitary())</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;  {</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::people::GroundBasedPeopleDetectionApp::setCloudTransform] The cloud transformation matrix must be an orthogonal matrix!\n&quot;</span>);</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;  }</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160; </div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ad38c3910bab88bbc45151ae6ec34fa9e">transformation_</a> = transformation;</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a3755cf5e032e685eab28df94aa14113c">transformation_set_</a> = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ad88876b8e9f69b703ffc26d1d5c92760">applyTransformationGround</a>();</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a0dc924992669bcd76b7dad68cfd5c5f6">applyTransformationIntrinsics</a>();</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_a3755cf5e032e685eab28df94aa14113c"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a3755cf5e032e685eab28df94aa14113c">pcl::people::GroundBasedPeopleDetectionApp::transformation_set_</a></div><div class="ttdeci">bool transformation_set_</div><div class="ttdoc">flag stating whether the transformation matrix has been set or not</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:309</div></div>
<div class="ttc" id="aclasspcl_1_1people_1_1_ground_based_people_detection_app_html_ad38c3910bab88bbc45151ae6ec34fa9e"><div class="ttname"><a href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#ad38c3910bab88bbc45151ae6ec34fa9e">pcl::people::GroundBasedPeopleDetectionApp::transformation_</a></div><div class="ttdeci">Eigen::Matrix3f transformation_</div><div class="ttdoc">rotation matrix which transforms input point cloud to internal people tracker coordinate frame</div><div class="ttdef"><b>Definition:</b> ground_based_people_detection_app.h:306</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a5280579c14550268bd5b64a01f5716b5">&#9670;&nbsp;</a></span>setVoxelSize()</h2>

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<div class="memtemplate">
template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setVoxelSize </td>
          <td>(</td>
          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>voxel_size</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Set voxel size. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">voxel_size</td><td>Value of the voxel dimension (default = 0.06m.). </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;{</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a9dfb9076a6111ff4588a554d83ef9971">voxel_size_</a> = voxel_size;</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;  <a class="code" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html#a74d6d3cb5fd914ed35b0d23702719912">updateMinMaxPoints</a> ();</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;}</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a60516702b769124ed3da3fd318258ba0">&#9670;&nbsp;</a></span>swapDimensions()</h2>

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template&lt;typename PointT &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1people_1_1_ground_based_people_detection_app.html">pcl::people::GroundBasedPeopleDetectionApp</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::swapDimensions </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_r_g_b.html">pcl::RGB</a> &gt;::Ptr &amp;&#160;</td>
          <td class="paramname"><em>cloud</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Swap rows/cols dimensions of a <a class="el" href="structpcl_1_1_r_g_b.html" title="A structure representing RGB color information.">RGB</a> point cloud (90 degrees counterclockwise rotation). </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in,out]</td><td class="paramname">cloud</td><td>A pointer to a <a class="el" href="structpcl_1_1_r_g_b.html" title="A structure representing RGB color information.">RGB</a> point cloud. </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;{</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;  pcl::PointCloud&lt;pcl::RGB&gt;::Ptr output_cloud(<span class="keyword">new</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt;pcl::RGB&gt;</a>);</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;  output_cloud-&gt;points.resize(cloud-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#a4f34b45220c57f96607513ffad0d9582">height</a>*cloud-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#a2185a6453f8ad905d7bdf7b45754a160">width</a>);</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;  output_cloud-&gt;width = cloud-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#a4f34b45220c57f96607513ffad0d9582">height</a>;</div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;  output_cloud-&gt;height = cloud-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#a2185a6453f8ad905d7bdf7b45754a160">width</a>;</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;  <span class="keywordflow">for</span> (uint32_t i = 0; i &lt; cloud-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#a2185a6453f8ad905d7bdf7b45754a160">width</a>; i++)</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;  {</div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;    <span class="keywordflow">for</span> (uint32_t j = 0; j &lt; cloud-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#a4f34b45220c57f96607513ffad0d9582">height</a>; j++)</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;    {</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;      (*output_cloud)(j,i) = (*cloud)(cloud-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#a2185a6453f8ad905d7bdf7b45754a160">width</a> - i - 1, j);</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;    }</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;  }</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;  cloud = output_cloud;</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;}</div>
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<hr/>该类的文档由以下文件生成:<ul>
<li>people/include/pcl/people/<a class="el" href="ground__based__people__detection__app_8h_source.html">ground_based_people_detection_app.h</a></li>
<li>people/include/pcl/people/impl/<a class="el" href="ground__based__people__detection__app_8hpp_source.html">ground_based_people_detection_app.hpp</a></li>
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